Population

In this Notebook, we will be looking at the population and it’s distribution in Freiberg. The Data is from the 2011 Census.

cfg = ConfigObj(r"..\notebook.ini")

csv10m = Path((Path(".").parent), "csvs", "Freiberg, Sachsen-10m.csv")
df = pd.read_csv(csv10m)
df.columns = ["id", "lon", "lat", "pop"]
df = df.set_index("id")
df

	lon	lat	pop
id
0	13.327293	50.875905	0.80
1	13.327435	50.875905	0.80
2	13.327577	50.875905	0.80
3	13.327719	50.875905	0.80
4	13.327862	50.875905	0.80
...	...	...	...
107095	13.330049	50.944991	0.03
107096	13.330191	50.944991	0.03
107097	13.330333	50.944991	0.03
107098	13.330475	50.944991	0.03
107099	13.330617	50.944991	0.03

107100 rows × 3 columns

fig, ax = plt.subplots(figsize=(16, 12))
ax = df.plot.hexbin(x="lon",
                    y="lat",
                    C="pop",
                    reduce_C_function=np.sum,
                    gridsize=50,
                    ax=ax)

tags = {"type": "boundary"}
place = "Freiberg, Sachsen"
# gdf = ox.geometries_from_place(, tags)
# gdf.plot()
bbox = ox.geocoder.geocode_to_gdf(place, buffer_dist=200)
geom = bbox.geometry.loc[0]

p = gpd.GeoSeries(geom).geometry.boundary
ax = p.plot(color=None, edgecolor='k', linewidth=2, ax=ax)
figure = ax.get_figure()
figure

<Figure size 640x480 with 0 Axes>

def heat_map(df):
    # lat/long/weight

    try:
        data = df[["lat", "lon", "pop"]]
    except KeyError:
        data = df[["x", "y", "einwohner"]]

    # print(df["2"].max())

    m = folium.Map([50.9, 13.37], zoom_start=12)

    HeatMap(data, min_opacity=0.4,
            gradient={.4: 'blue', .8: 'lime',
                      0.9: 'yellow', 0.95: 'orange', 1: 'red'}
            ).add_to(folium.FeatureGroup(name='Heat Map').add_to(m))
    folium.LayerControl().add_to(m)

    # m.save('{0}.html'.format('Freiberg-census-10m'))
    return m

heat_map(df)

Make this Notebook Trusted to load map: File -> Trust Notebook

cfg = ConfigObj("notebook.ini")
scenarios = cfr.get_scenarios(cfg)
G = oh.get_place(placename=place, simplify=True,
                 clean_periphery=True,
                 file_identifier="", retain_all=True)

G_nx = r4r.load_pop_scenario(cfg, G, place, "Small")
to_remove = []
for node in G_nx.nodes():
    try:
        G_nx.nodes[node]["pop"]
    except KeyError:
        to_remove.append(node)

G.remove_nodes_from(to_remove)
x = ox.plot_graph(G,
                  figsize=(16, 12),
                  node_color=ox.plot.get_node_colors_by_attr(G, "pop"),
                  node_size=5,
                  edge_linewidth=0.1)
x

(<Figure size 1600x1200 with 1 Axes>, <Axes: >)

G = oh.get_place(placename=place, simplify=True,
                 clean_periphery=True,
                 file_identifier="", retain_all=True)
G_nx = r4r.load_pop_scenario(cfg, G, place, "Small")
to_remove = []
for node in G_nx.nodes():
    try:
        G_nx.nodes[node]["pop"]
    except KeyError:
        to_remove.append(node)

G.remove_nodes_from(to_remove)
x = ox.plot_graph(G,
                  figsize=(16, 12),
                  node_color=ox.plot.get_node_colors_by_attr(G, "pop"),
                  node_size=5,
                  edge_linewidth=0.1)
x

(<Figure size 1600x1200 with 1 Axes>, <Axes: >)

G = oh.get_place(placename=place, simplify=True,
                 clean_periphery=True,
                 file_identifier="", retain_all=True)
G_nx = r4r.load_pop_scenario(cfg, G, place, "Medium")
to_remove = []
for node in G_nx.nodes():
    try:
        G_nx.nodes[node]["pop"]
    except KeyError:
        to_remove.append(node)

G.remove_nodes_from(to_remove)
x = ox.plot_graph(G,
                  figsize=(16, 12),
                  node_color=ox.plot.get_node_colors_by_attr(G, "pop"),
                  node_size=5,
                  edge_linewidth=0.1)
x

(<Figure size 1600x1200 with 1 Axes>, <Axes: >)

G = oh.get_place(placename=place, simplify=True,
                 clean_periphery=True,
                 file_identifier="", retain_all=True)
G_nx = r4r.load_pop_scenario(cfg, G, place, "Medium-restricted")
to_remove = []
for node in G_nx.nodes():
    try:
        G_nx.nodes[node]["pop"]
    except KeyError:
        to_remove.append(node)

G.remove_nodes_from(to_remove)
x = ox.plot_graph(G,
                  figsize=(16, 12),
                  node_color=ox.plot.get_node_colors_by_attr(G, "pop"),
                  node_size=5,
                  edge_linewidth=0.1)
x

(<Figure size 1600x1200 with 1 Axes>, <Axes: >)

G = oh.get_place(placename=place, simplify=True,
                 clean_periphery=True,
                 file_identifier="", retain_all=True)
G_nx = r4r.load_pop_scenario(cfg, G, place, "Large")
to_remove = []
for node in G_nx.nodes():
    try:
        G_nx.nodes[node]["pop"]
    except KeyError:
        to_remove.append(node)

G.remove_nodes_from(to_remove)
x = ox.plot_graph(G,
                  figsize=(16, 12),
                  node_color=ox.plot.get_node_colors_by_attr(G, "pop"),
                  node_size=5,
                  edge_linewidth=0.1)
x

(<Figure size 1600x1200 with 1 Axes>, <Axes: >)

G = oh.get_place(placename=place, simplify=True,
                 clean_periphery=True,
                 file_identifier="", retain_all=True)
G_nx = r4r.load_pop_scenario(cfg, G, place, "Optimal")
to_remove = []
for node in G_nx.nodes():
    try:
        G_nx.nodes[node]["pop"]
    except KeyError:
        to_remove.append(node)

G.remove_nodes_from(to_remove)
x = ox.plot_graph(G,
                  figsize=(16, 12),
                  node_color=ox.plot.get_node_colors_by_attr(G, "pop"),
                  node_size=5,
                  edge_linewidth=0.1)
x

(<Figure size 1600x1200 with 1 Axes>, <Axes: >)